Automatic node hardware configuration in a distributed storage system

ABSTRACT

A method for execution by one or more processing modules of one or more computing devices of a dispersed storage network (DSN), the method begins by determining a DSN node configuration automatically during deployment. The method continues by modifying the DSN node configuration to enable/disable specific hardware features. The method continues by modifying the DSN node configuration to test hardware failure scenarios. The method continues by modifying the DSN node configuration for component replacement procedures. The method continues by reporting the modified DSN node configuration to a DSN management unit and providing a status on component and health of the DSN node to an operator of the DSN.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of an example of distributed storagenetwork node configurations in accordance with the present invention;and

FIG. 9A is a diagram illustrating an example of distributed storagenetwork node configuration in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-9A. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSTN memory 22for a user device, a group of devices, or for public access andestablishes per vault dispersed storage (DS) error encoding parametersfor a vault. The managing unit 18 facilitates storage of DS errorencoding parameters for each vault by updating registry information ofthe DSN 10, where the registry information may be stored in the DSNmemory 22, a computing device 12-16, the managing unit 18, and/or theintegrity processing unit 20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN memory 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generateper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSTN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 60 is shown inFIG. 6. As shown, the slice name (SN) 60 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of an example of distributed storagenetwork node configurations in accordance with the present invention.Dispersed storage network (DSN) 10 includes at least DSN managing unit18, DSN memory 22 apportioned into (sites (1-n)) each with a subset of aplurality of DS storage units (1-N). Each storage unit also includes aplurality of DSN memories M-1 through M-N (e.g., hard drives, staticmemory, solid state memory, optical memory, etc.) storing encoded dataslices. DSN managing unit 18 is communicatively connected to sites 1-nthrough network 24 of FIG. 1. In this example embodiment, six DS storageunits (storing pillar 0-pillar N) are located at three different sites;pillars 0-1 are located at site 1, pillars 2-3 are located at site 2,and pillars 4-N are located at site N.

DSN managing unit 18 includes the computing core 26 and memory 54 ofFIG. 2 and an interface, which can include, for example, interface 30,32, and/or 33 of FIG. 1. Each DSN storage site (1-n) can include thesame number or a different number of storage units k. Each DSN memorycan, for example, be utilized by DSN memory 22 of FIG. 1, and eachstorage unit can, for example, be utilized by storage unit 36 of FIG. 1.

The DSN includes a multitude of storage nodes for storage of dataobjects (as encoded data slices). The multitude of storage nodes may beorganized into one or more storage node sets. Each storage node of theplurality of storage nodes may be implemented utilizing at least one ofa storage server, a storage unit, a storage module, a memory device, amemory, a distributed storage (DS) unit, a DS processing unit, adistributed storage and task (DST) execution unit, a user device, a DSTprocessing unit, and a DST processing module.

Components and memory devices will eventually degrade in a DSN memory.When this occurs, remote system operators need to communicate how toperform remediation actions to the on-site technicians. The technologydescribed herein provides a mechanism to simplify this process.

In traditional systems and DSNs, nodes have different properties thatrequire specific knowledge to perform operations on how to replacefailing components and accurately gauge the health of the node. To easethe process of completing remediation actions, a DSN node is configuredautomatically at deployment time. A system operator can modify this DSNnode configuration 902 to enable/disable specific hardware features, andmay manipulate the behavior of a node by modifying the DSN nodeconfiguration of any node to test hardware failure scenarios andcomponent replacement procedures. The DSN node reports its configuration902 to the DSN management unit 18 using a DSN management protocol. TheDSN management unit then uses that configuration to provide the operatorwith status on component and DSN node health.

By having the DSN node report the specifics of the hardware properties,the DSN management unit can generate health checks to be tailored to anindividual DSN node configuration without prior knowledge of the DSNnode hardware properties. The DSN node configuration allows forfine-tuning of node behavior based on its hardware characteristics andenables the operator to support a variety of node classes with varioushardware properties through a DSN management interface. In addition,nodes in a DSN may have their own hardware vendor supplied managementprotocol which are not interoperable with each other, making itdifficult for an operator to understand the implications of node healthon the DSN system. By enabling node-specific property monitoring, theoperator can better gauge the health and reliability of their DSN andcan more proactively perform replacement operations on failedcomponents.

For a DSN memory containing a set of hardware components, operators maynot have the knowledge required to assess the health without knowledgeof the underlying hardware. This mechanism enables a DSN operator tounderstand the health of an individual DSN node health without requiringprior knowledge of the DSN node. By abstracting the hardware specificknowledge (e.g., hardware abstraction layer (HAL)) of a node throughautomatic configuration at the time of deployment, the operator does notrequire intimate knowledge of the hardware of a DSN memory during theproduct lifecycle. Hardware abstractions can include sets of routines insoftware that emulate some hardware-specific details, giving programsdirect access to the hardware resources. One function is to hidedifferences in hardware from most of the operating system kernel, sothat most of the kernel-mode code does not need to be changed to run onsystems with different hardware.

Typically, DSN managing unit 18 is responsible for memory management,monitoring, and debugging across multiple DSN components and memories.In various embodiments, DSN managing unit 18 performs memory management,monitoring, and debugging by transmitting DSN node configuration updaterequests to each DSN node (e.g., DSN site(s) or DS storage unit(s)),which in turn push appropriate update requests to the DSN nodes. Inresponse, the DSN nodes can transmit requested logs and/or statisticsback to DSN management unit 18 for aggregation, analysis, and/orstorage.

DSN nodes are configured during deployment with the DSN nodeconfigurations reported to the DSN management unit 18 as hardwareabstractions with operator modifications based on specific hardwarefeatures, hardware failure scenarios or component replacementprocedures. Management unit 18 receives modified node configurationsbased on a DSN management protocol and can provide operators with astatus on component and node health.

DSN node configuration parameters can specify a hardware abstractionconfiguration update to one or more DSN components of the DSN node, suchas one or more storage units, one or more computing devices, one or moreintegrity processing units 20 of FIG. 1, one or more managing units 18of FIG. 1, or other components present in the DSN. The configurationparameters can further specify component parameters of the one of morecomponents to be enabled or overridden, specify new values the componentparameters should be set to, specify which software releases to applyagainst, and/or specify the set of components to which the updateapplies.

In various embodiments, data from DSN nodes, such as logs and/orstatistics, are desired for the purpose of monitoring changes in the DSNnodes, for example, to monitor DSN node configuration updates or nodehealth related issues. The DSN configuration parameters can indicate aset of statistics and/or logs to collect, what time frames to collectover, and/or other information relating to statistics collection fromone or more DSN nodes and/or components in the DSN. The specifiedstatistics and/logs can be based on data that would be specificallyrelevant to the DSN node configuration. Each DSN node unit canperiodically communicate with DSN management unit 18 and/or a particularinstance to receive the latest configuration abstraction and relatedhealth of components of the node.

In various embodiments, DSN managing unit 18, upon receiving the logsand/or statistics from each managing unit, can further parse, filter,aggregate, and/or compress the data. DSN managing unit 18 can performanalysis, such as searching for health of components in the data,organizing and/or categorizing data, and/or determining or projectingwhen future storage may be needed (e.g., upgrades).

FIG. 9A is a diagram illustrating an example of distributed storagenetwork node configuration. In particular, a method is presented for usein conjunction with one or more functions and features described inconjunction with FIGS. 1-2, 3-8, and also FIG. 9.

The method illustrated is for execution by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN). The method begins in step 920 by determining a DSN nodeconfiguration automatically during deployment. DSN nodes are configuredduring deployment with the DSN node configurations reported to the DSNmanagement unit 18 as hardware abstractions with modifications based onhardware features, hardware failure scenarios or component replacementprocedures as further described below.

The method continues in step 922 by modifying the DSN node configurationto enable/disable specific hardware features. The DSN node configurationparameters can specify a hardware abstraction configuration update toone or more DSN components of the DSN node, such as one or more storageunits, one or more computing devices, one or more integrity processingunits 20 of FIG. 1, one or more managing units 18 of FIG. 1, or othercomponents present in the DSN node. The configuration parameters canfurther specify component parameters of the one of more components to beenabled or overridden, specify new values the component parametersshould be set to, specify which software releases to apply against,and/or specify the set of components to which the configuration updateapplies.

The method continues in step 924 by modifying the DSN node configurationto test hardware failure scenarios. The hardware failure scenarios canbe any of known or predicted: hardware specific failures, locationspecific failures, environment specific failures (e.g., temperature,humidity, weather, etc.), age of components at time of deployment,generation of components, compatibility with existing or new components,etc.). Modifying the DSN node configuration for hardware failurescenarios can, in one embodiment, change the behavior of the DSN node.

The method continues in step 926 by modifying the DSN node configurationfor component replacement procedures. Modifying the DSN nodeconfiguration for component replacement procedures can, in oneembodiment, change the behavior of the DSN node.

The method continues in step 928 by reporting the modified DSN nodeconfiguration to a DSN management unit. Management unit 18 receivesmodified node configurations based on a DSN management protocol and canprovide operators with a status on component and node health.

The method continues in step 930 by providing a status on componenthealth and overall health of the DSN node to an operator of the DSN.Data from DSN nodes, such as logs and/or statistics, are desired for thepurpose of monitoring changes in the DSN nodes, for example, to monitorDSN node updates or node/component health related issues. The DSNconfiguration parameters can indicate a set of statistics and/or logs tocollect, what time frames to collect over, and/or other informationrelating to statistics collection from one or more DSN nodes and/orcomponents in the DSN. The specified statistics and/logs can be based ondata that would be specifically relevant to the DSN node configuration.Each DSN node unit can periodically communicate with DSN management unit18 and/or a particular instance to receive the latest configurationabstraction and related health of components of the node.

The method described above in conjunction with the processing module canalternatively be performed by other modules of the dispersed storagenetwork or by other computing devices. In addition, at least one memorysection (e.g., a non-transitory computer readable storage medium) thatstores operational instructions can, when executed by one or moreprocessing modules of one or more computing devices of the dispersedstorage network (DSN), cause the one or more computing devices toperform any or all of the method steps described above.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, text, graphics, audio, etc. any of which may generally bereferred to as ‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. For some industries, anindustry-accepted tolerance is less than one percent and, for otherindustries, the industry-accepted tolerance is 10 percent or more. Otherexamples of industry-accepted tolerance range from less than one percentto fifty percent. Industry-accepted tolerances correspond to, but arenot limited to, component values, integrated circuit process variations,temperature variations, rise and fall times, thermal noise, dimensions,signaling errors, dropped packets, temperatures, pressures, materialcompositions, and/or performance metrics. Within an industry, tolerancevariances of accepted tolerances may be more or less than a percentagelevel (e.g., dimension tolerance of less than +/−1%). Some relativitybetween items may range from a difference of less than a percentagelevel to a few percent. Other relativity between items may range from adifference of a few percent to magnitude of differences.

As may also be used herein, the term(s) “configured to”, “operablycoupled to”, “coupled to”, and/or “coupling” includes direct couplingbetween items and/or indirect coupling between items via an interveningitem (e.g., an item includes, but is not limited to, a component, anelement, a circuit, and/or a module) where, for an example of indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.

As may even further be used herein, the term “configured to”, “operableto”, “coupled to”, or “operably coupled to” indicates that an itemincludes one or more of power connections, input(s), output(s), etc., toperform, when activated, one or more its corresponding functions and mayfurther include inferred coupling to one or more other items. As maystill further be used herein, the term “associated with”, includesdirect and/or indirect coupling of separate items and/or one item beingembedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may be used herein, one or more claims may include, in a specificform of this generic form, the phrase “at least one of a, b, and c” orof this generic form “at least one of a, b, or c”, with more or lesselements than “a”, “b”, and “c”. In either phrasing, the phrases are tobe interpreted identically. In particular, “at least one of a, b, and c”is equivalent to “at least one of a, b, or c” and shall mean a, b,and/or c. As an example, it means: “a” only, “b” only, “c” only, “a” and“b”, “a” and “c”, “b” and “c”, and/or “a”, “b”, and “c”.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, “processing circuitry”, and/or “processing unit”may be a single processing device or a plurality of processing devices.Such a processing device may be a microprocessor, micro-controller,digital signal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, processing circuitry, and/or processing unitmay be, or further include, memory and/or an integrated memory element,which may be a single memory device, a plurality of memory devices,and/or embedded circuitry of another processing module, module,processing circuit, processing circuitry, and/or processing unit. Such amemory device may be a read-only memory, random access memory, volatilememory, non-volatile memory, static memory, dynamic memory, flashmemory, cache memory, and/or any device that stores digital information.Note that if the processing module, module, processing circuit,processing circuitry, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,processing circuitry and/or processing unit implements one or more ofits functions via a state machine, analog circuitry, digital circuitry,and/or logic circuitry, the memory and/or memory element storing thecorresponding operational instructions may be embedded within, orexternal to, the circuitry comprising the state machine, analogcircuitry, digital circuitry, and/or logic circuitry. Still further notethat, the memory element may store, and the processing module, module,processing circuit, processing circuitry and/or processing unitexecutes, hard coded and/or operational instructions corresponding to atleast some of the steps and/or functions illustrated in one or more ofthe Figures. Such a memory device or memory element can be included inan article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with one or more other routines. In addition, a flow diagrammay include an “end” and/or “continue” indication. The “end” and/or“continue” indications reflect that the steps presented can end asdescribed and shown or optionally be incorporated in or otherwise usedin conjunction with one or more other routines. In this context, “start”indicates the beginning of the first step presented and may be precededby other activities not specifically shown. Further, the “continue”indication reflects that the steps presented may be performed multipletimes and/or may be succeeded by other activities not specificallyshown. Further, while a flow diagram indicates a particular ordering ofsteps, other orderings are likewise possible provided that theprinciples of causality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form asolid-state memory, a hard drive memory, cloud memory, thumb drive,server memory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for configuring hardware within a datastorage network (DSN) comprising the steps of: configuring a DSN node atdeployment time within the DSN; reporting, via the DSN node, abstractedhardware configuration information to a DSN management unit; generating,via the DSN management unit, health checks tailored to the DSN nodebased upon the abstracted hardware configuration information; andreporting, via the DSN management unit, a status of components and DSNnode health information, wherein DSN node configuration parametersspecify enabling or overriding component parameters of one of morecomponents of the DSN node, specify new values for the componentparameters, specify which software releases to apply against, andspecify a set of components of the DSN node which a configuration updateapplies.
 2. The method of claim 1, wherein the configuring the DSN nodeis performed automatically at the deployment time.
 3. The method ofclaim 1, further comprising modifying the abstracted hardwareconfiguration information to enable/disable specific hardware featuresof the DSN.
 4. The method of claim 1, further comprising: modifying theabstracted hardware configuration information based on testing hardwarefailure scenarios; transmitting, via the DSN node, logs and statisticsback to the DSN management unit for aggregation, analysis, and storageas monitoring changes in the DSN node; and parsing, filtering,aggregating, and compressing, via the DSN management unit, the logs andstatistics received at the DSN management unit from the DSN node.
 5. Themethod of claim 4, wherein the testing hardware failure scenariosinclude any of known or predicted: hardware specific failures, locationspecific failures, environment specific failures, age of components attime of deployment, generation of components, or compatibility withexisting or new components.
 6. The method of claim 1, furthercomprising: modifying the DSN node configuration for componentreplacement procedures; rebuilding, via an integrity processing unit,encoded data slices of a DSN memory of the DSN by periodicallyattempting to retrieve encoded data slices and slice names of theencoded data slices and checking the encoded data slices which areretrieved for errors due to data corruption; and creating and storing,via the DSN management unit, user profile information within the DSNmemory, wherein the rebuilding encoded data slices includes using otherretrieved encoded data slices to produce rebuilt slices, the userprofile information includes authentication information, permissions,and security parameters, and the security parameters include anencryption scheme, one or more encryption keys, a key generation scheme,and a data encoding scheme.
 7. The method of claim 1, wherein thereporting, via the DSN node, the abstracted hardware configurationinformation to the DSN management unit reporting with a DSN managementprotocol.
 8. The method of claim 1, wherein the reporting, via the DSNmanagement unit, of the status of components and the DSN node healthinformation is communicated to an operator of the DSN.
 9. A computingdevice of a group of computing devices of a dispersed storage network(DSN), the computing device comprises: an interface; a local memory; anda processing module operably coupled to the interface and the localmemory, wherein the processing module functions to: configure a DSN nodeat deployment time within the DSN; report, via the DSN node, abstractedhardware configuration information to a DSN management unit; generate,via the DSN management unit, health checks tailored to the DSN nodebased upon the abstracted hardware configuration information; andreport, via the DSN management unit, a status of components and DSN nodehealth information, wherein DSN node configuration parameters specifyenabling or overriding component parameters of one of more components ofthe DSN node, specify new values for the component parameters, specifywhich software releases to apply against, and specify a set ofcomponents of the DSN node which a configuration update applies.
 10. Thecomputing device of claim 9, wherein the configure the DSN node isperformed automatically at the deployment time.
 11. The computing deviceof claim 9, further comprises modifying the abstracted hardwareconfiguration information to enable/disable specific hardware features.12. The computing device of claim 9, further comprises modifying theabstracted hardware configuration information based on testing hardwarefailure scenarios.
 13. The computing device of claim 12, wherein thetesting hardware failure scenarios include any of known or predicted:hardware specific failures, location specific failures, environmentspecific failures, age of components at time of deployment, generationof components, or compatibility with existing or new components.
 14. Thecomputing device of claim 9, further comprises modifying the abstractedhardware configuration information for component replacement procedures.15. The computing device of claim 9, wherein the report, via the DSNnode, the abstracted hardware configuration information to the DSNmanagement unit includes reporting with a DSN management protocol. 16.The computing device of claim 9, wherein the report, via the DSNmanagement unit, of the status of components and the DSN node healthinformation is communicated to an operator of the DSN.
 17. A method forexecution by one or more processing modules of one or more computingdevices of a dispersed storage network (DSN), the method comprises:determining a DSN node configuration based on abstracted hardwareconfiguration information; modifying the DSN node configuration toenable/disable specific hardware features; modifying the DSN nodeconfiguration to test hardware failure scenarios; modifying the DSN nodeconfiguration for component replacement procedures; reporting themodified DSN node configuration to a DSN management unit; and providinga status on component and health of the DSN node, wherein DSN nodeconfiguration parameters specify enabling or overriding componentparameters of one of more components of the DSN node, specify new valuesfor the component parameters, specify which software releases to applyagainst, and specify a set of components of the DSN node which aconfiguration update applies.
 18. The method of claim 17, wherein thedetermining the DSN node configuration is performed automatically atdeployment time.
 19. The method of claim 17, wherein the reporting themodified DSN node configuration to the DSN management unit includesreporting with a DSN management protocol.
 20. The method of claim 17,wherein the providing the status on component and health of the DSN nodeis communicated to an operator of the DSN.